Opioid Use Disorder County Prevalence Using Recapture Estimates (OUD CAPTURE)
Official title: Opioid Use Disorder County Area Prevalence Through Use of Recapture Estimates (OUD CAPTURE)
Funded at University of Kentucky · NIH-11457463 · Data updated 2026-11-12
Aimed at estimating how common opioid use disorder is across counties using advanced statistical methods to help target treatment and resources.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Kentucky NIH-funded |
| Lab location | 1 site (Lexington, United States) |
| Project start | September 1, 2026 |
| Project end | June 30, 2031 |
| Funding year | 2026 |
| Award (this year) | $548,992 |
| NIH project number | 1R01DA064086-01A1 |
| Project ID | NIH-11457463 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates include communities and regions with uncertain or under-reported OUD prevalence where county-level estimates can inform policy and care.
✕Less likely to help
Communities with already precise, up-to-date county estimates and no need for estimation refinements may see limited direct benefit.
What this research studies
This project will apply recapture methods and Bayesian models to estimate county-level OUD prevalence for a large set of counties, using linked data from multiple states. It will compare different modeling approaches to determine which best reflects the true burden. The researchers will also explore how county-level OUD estimates relate to publicly available factors, with plans to project estimates to counties with missing data. The study involves recruiting additional states to broaden geographic coverage and improve precision for policy planning and resource allocation.
Why it matters
Potential benefit: If successful, it could provide more accurate county-level estimates of OUD to guide targeted treatment and resource distribution.
How similar studies have gone: Previous methods have shown promise in capturing unobserved cases and guiding resource allocation, with Bayesian approaches offering robust uncertainty quantification.
Where this research is happening
-
University of Kentucky
Lexington, United States Active
Researchers
- Principal investigator: Delcher, Chris — University of Kentucky
- Study coordinator: Delcher, Chris
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.